Foundations of Marketing with AI

This unit introduces the historical context, core technologies, and practical marketing applications of artificial intelligence. Students learn foundational concepts—data, machine learning, neural networks, NLP, generative models, and analytics techniques—and begin applying them to customer service automation, segmentation, testing, personalization, and ethical integration planning.

Learning Objectives

• Analyze historical technological advances and core AI architectures (machine learning, neural networks, NLP, GPTs, and quantum-assisted approaches) to explain their impacts on marketing strategy and operations
• Apply fundamental data and analytics concepts—including data definition, collection methods, predictive analytics, churn modeling, behavioral segmentation, and A/B testing—to construct data-driven marketing scenarios
• Demonstrate practical use of AI tools and techniques for marketing tasks such as automating customer service, generating creative content, building conversational interfaces, and leveraging localization and personalization features
• Evaluate ethical, legal, and operational considerations for integrating AI into marketing (data privacy, bias, qualitative insight handling, governance, and stepwise implementation) and recommend responsible adoption practices